1. Field of the Invention
The present invention relates to a speech recognition system and method and, more particularly, to a speech recognition system and method utilizing meta-information to improve accuracy of the system.
2. Description of Related Art
Correctly recognizing and responding to spoken natural language phrases is very difficult for automated systems. There are multiple sources of uncertainty that can arise from variability in the inputs, namely, variability in the quality and pronunciation of the speech, variability in the acquisition and processing of the speech input, and variability in the phrasing (the words used and their order) of the input. Prior art automated speech recognition technology is capable of assessing a numerical quality metric to individual words and phrases that it is attempting to recognize, thereby, indicating how confident it is that it has successfully recognized these individual words and phrases. Typically, this numerical quality metric will be made available in the text output of the speech recognition technology to give an indication of the confidence of the recognition of each of the elements output.
However, the problem of correctly understanding a spoken phrase extends beyond the problem of identifying just the spoken words. The number of ways that a request can be phrased by a user is virtually unbounded. Prior art automated speech recognition systems treat the uncertainty in speech and the uncertainty in phrasing with a single approach that attempts to compensate for both simultaneously, or they avoid the problem of phrasing uncertainty altogether by forcing the user to a highly constrained format for making requests.
It is, therefore, desirable to overcome the above problems and others by providing a more accurate and efficient speech recognition system and method directed thereto.